Journal of Information Processing Systems, Vol.8, No.3, September 2012 http://dx.doi.org/10.3745/JIPS.2012.8.3.445 445 Iris Recognition Using Ridgelets Lenina Birgale* and Manesh Kokare** Abstract—Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR. Keywords—Ridgelets, Texture, Wavelets, Biometrics, Features, Database 1. INTRODUCTION Security systems are the need of the day. Efficient and fast recognition systems are the de- mand of the current era. Facial features, voice patterns, hand geometry, retinal patters, vein pat- terns, signature dynamics, voice verification, facial thermographs, DNA matching nail-bed iden- tification, gait recognition, ear shape recognition, and finger prints have all been explored as biometric identifiers with varying levels of success. However irises, which are unique and stable for the duration of a person's life, have emerged as the most reliable biometric. Irises as a bio- metric for identification have been an active research area since 1992. The uniqueness of iris patterns was identified by A. Muron and J. Pospisil, [1-5]. This uniqueness property of irises can be explained in the words of Daugman [6, 7] as, “An advantage that the iris shares with finger prints is the chaotic morphogenesis of its minutiae.” The iris can be identified as the colored portion of the eye lying between the pupil and sclera. A frontal view of the human eye is shown in Fig. 1. A very important characteristic of an iris is that it is a naturally protected organ and is stable without any variations including effects of an individual aging. It is the source of abun- dant textural information. This texture has to be exploited completely for a better biometric sys- tem design. Traditional methods are computationally expensive. Hence the challenge in an iris recognition system is to develop a fast responding and computationally inexpensive system for online applications. The reduction of computational complexity, without losing track of other system performance parameters, motivates us to solve this problem [1]. Though wavelets detect point singularities, they are computationally expensive as demonstrated by Terrades and Manuscript received Octorber 27, 2011; accepted March 8, 2012. Corresponding Author: Lenina Birgale * Dept. of Electronics and Telecommunication Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Vishnupuri, Nanded, Maharashtra State, India (lenina2003_2003@yahoo.com, mbkokare@sggs.ac.in) Copyright ⓒ 2012 KIPS (ISSN 1976-913X)